POVERTY REDUCTION STRATEGY TN

influence of increased

influence of increased income inequality is relatively larger, but the influence of growth is predominant. Table 2.9 shows that inequality in urban incomes is much higher than that in rural incomes. To update the official poverty line used by the Planning Commission, the Consumer Price Index for Africultural Laborers (CPI-AL) and the Consumer Price Index for Industrial Workers (CPI-IW) are reweighted using national level consumption patterns of people around the poverty line in 1973-74. The basic price data are the same as for CPI-AL and CPI-IW, but the commodity level prices are weighted using the more recent and more poverty relevant weights. States Table 2.9: Growth and the Head Count Ratio: 1993-94 to 1999-00 HCR50 Derivative with Respect to Growth Six Years Growth Change in HCR55 Inequality Fixed Change in HCR55 Actual Rural Andhra Pradesh 29.2 -0.9 2.8 -2.5 -3 Karnataka 37.9 -0.91 9.5 -9 -7.2 Kerala 19.5 -0.62 19.6 -10.3 -9.5 Tamil Nadu 38.5 -0.9 15.7 -13.3 -14.1 All India 33 -0.88 8.7 -6.8 -6.7 Urban Andhra Pradesh 17.8 -0.62 18.5 -9 -6.9 Karnataka 21.4 -0.6 26.5 -12.9 -10.6 Kerala 13.9 -0.46 18.2 -7.1 -4.2 Tamil Nadu 20.8 -0.66 25.1 -12.9 -9.6 All India 17.8 -0.56 16.6 -7.4 -5.9 Source: Deaton and Dreze (2002). HCR50 and HCR55 - Head Count Ratio from 50 th Round and 55 th round, respectively. Bhalla (2002) uses the concept of ‘Shape of Distribution Elasticity’ (SDE), which indicates proportionate change in the HCR, following a one percent change in growth, assuming that there is no change in the distribution. He defines: dP = (g + i)* SDE where dP is the change in the head count ratio, g is the growth in average per capita consumption and i is the change in the share of consumption of the poor on or near the poverty line. Bhalla (2003) argues that the kind of elasticities estimated by Ravallion and 40